Signal processing techniques for an accelerometer signal?

1. What are signal processing techniques?
2. What is accelerometer data processing?
3. What can you do with accelerometer data?
4. How do you remove noise from accelerometer data?

What are signal processing techniques?

Signal processing techniques are used to optimize transmissions, digital storage efficiency, correcting distorted signals, subjective video quality and to also detect or pinpoint components of interest in a measured signal.

What is accelerometer data processing?

Accelerometers are wearable devices that measure accelerations of the body segment to which the monitor is attached. The signal is usually filtered and pre-processed by the monitor to obtain activity counts, i.e., accelerations due to body movement.

What can you do with accelerometer data?

Accelerometers can be used to measure vibration on cars, machines, buildings, process control systems and safety installations. They can also be used to measure seismic activity, inclination, machine vibration, dynamic distance and speed with or without the influence of gravity.

How do you remove noise from accelerometer data?

You can start with a low-pass filter. Ask yourself what is the maximum frequency possible (it depends of where the accelerometer is) and filter out all frequencies above that. The cut-off frequency will be a few Hz. You will need a colleague with some signal processing background to help you implement the LP filter.